DbSchema | How to Implement JOINS in PostgreSQL?

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Table of Contents

1. Introduction
2. Prerequisites
3. What is a Join?
4. Usage of Joins
5. Advantages and Limitations of Using Joins
6. Restrictions on Using Joins
7. Types of Joins
8. Implementing Joins in psql
9. Implementing Joins in DbSchema
10. Conclusion
11. References

Introduction

When working with __relational databases, the ability to combine data from multiple tables is crucial. This is where the concept of __joins comes into play. In this article, we will explore how to implement joins in __psql (PostgreSQL's command-line interface) and __DbSchema, a popular database management and design tool.

Prerequisites

Before diving into the implementation of joins, ensure that you have the following prerequisites in place:

• A __PostgreSQL` database installed and running.
• __psql (PostgreSQL command-line interface) installed or access to a tool like __DbSchema that supports SQL querying.

For installation and establishing connection refer to PostgreSQL-How to create a database?

What is a Join?

In database management systems, a __join is a method to combine rows from two or more tables based on a related column between them. It allows us to query and __retrieve data from multiple tables as if they were a single table.

Usage of Joins

Joins are commonly used in the following scenarios:

• Retrieving related data from multiple tables.
• Combining data to generate meaningful reports.
• Filtering data based on specific conditions that involve multiple tables.

Advantages and Limitations of Using Joins

Advantages:

Advantages of using joins include:

• Simplifies querying by combining related data from multiple tables.
• Reduces data redundancy by storing data in __normalized form`.
• Allows for efficient __data retrieval and __analysis.

Limitations:

Limitations of using joins include:

• Performance impact on large datasets if not properly __optimized`.
• Complexity increases as the number of tables and conditions grow.
• May require careful consideration of __indexing and __query optimization techniques.

Restrictions on Using Joins

While joins offer powerful data retrieval capabilities, there are a few restrictions to keep in mind:

• Joining tables requires a __common column or __relationship between them.
• Columns used for joining tables should have the __same data type or __compatible data types.
• Join conditions should be __well-defined to avoid unexpected results or __Cartesian products.

Types of Joins

Join Type	Description
__Inner Join`	Returns only the matching rows from both tables.
__Left Join`	Returns all rows from the left table and the matching rows from the right table.
__Right Join`	Returns all rows from the right table and the matching rows from the left table.
__Full Outer Join`	Returns all rows from both tables, including unmatched rows.
Cross Join	Returns the Cartesian product of both tables, combining every row from the left table with every row from the right table.
Natural Join	Performs a join based on columns with the same name in both tables.
Self Join	Joins a table with itself, treating it as two separate tables, typically using aliases.

Implementing Joins in psql

To implement Joins in psql follow the steps mentioned below:

1. Launch the psql command-line interface.

2. Connect to your PostgreSQL database.
   For establishing connection refer to PostgreSQL-How to create a database?

3. Write the join query using the JOIN keyword and the appropriate join condition.

Sample Database:

basket_a Table:

a integer	fruit_a character varying(100)
1	Apple
2	Orange
3	Banana
4	Cucumber

basket_b Table:

b integer	fruit_b character varying(100)
1	Orange
2	Apple
3	Watermelon
4	Pear

Inner Join

The inner join selects records that have matching values in both tables.

SELECT *
FROM table1
INNER JOIN table2
ON table1.column = table2.column;

Example:

SELECT
    a,
    fruit_a,
    b,
    fruit_b
FROM
    basket_a
INNER JOIN basket_b
    ON fruit_a = fruit_b;

Result from Query:

Following is the result obtained by executing query on the sample database

a integer	fruit_a character varying(100)	b integer	fruit_b character varying(100)
1	Apple	2	Apple
2	Orange	1	Orange

Left Join

The left join returns all records from the left table and the matching records from the right table.

SELECT *
FROM table1
LEFT JOIN table2
ON table1.column = table2.column;

Example:

SELECT
    a,
    fruit_a,
    b,
    fruit_b
FROM
    basket_a
LEFT JOIN basket_b 
   ON fruit_a = fruit_b;

Result from Query:

Following is the result obtained by executing query on the sample database

a integer	fruit_a character varying(100)	b integer	fruit_b character varying(100)
1	Apple	2	Apple
2	Orange	1	Orange
3	Banana	[null]	[null]
2	Orange	[null]	[null]

Right Join

The right join returns all records from the right table and the matching records from the left table.

SELECT *
FROM table1
RIGHT JOIN table2
ON table1.column = table2.column;

Example:

SELECT
    a,
    fruit_a,
    b,
    fruit_b
FROM
    basket_a
RIGHT JOIN basket_b ON fruit_a = fruit_b;

Result from Query:

Following is the result obtained by executing query on the sample database

a integer	fruit_a character varying(100)	b integer	fruit_b character varying(100)
2	Orange	1	Orange
1	Apple	2	Apple
[null]	[null]	3	Watermelon
[null]	[null]	4	Pear

Full Outer Join

The full outer join returns all records from both tables, including unmatched records.

SELECT *
FROM table1
FULL OUTER JOIN table2
ON table1.column = table2.column;

Example:

SELECT
    a,
    fruit_a,
    b,
    fruit_b
FROM
    basket_a
FULL OUTER JOIN basket_b 
    ON fruit_a = fruit_b;

Result from Query:

Following is the result obtained by executing query on the sample database

a integer	fruit_a character varying(100)	b integer	fruit_b character varying(100)
2	Apple	2	Apple
1	Orange	1	Orange
3	Banana	[null]	[null]
4	Cucumber	[null]	[null]
[null]	[null]	3	Watermelon
[null]	[null]	4	Pear

Cross Join

The cross join returns the Cartesian product of both tables.

Sample Database:

customer Table:

customer_id	customer_name	customer_email
1	John Smith	john@example.com
2	Jane Doe	jane@example.com
3	Alice Brown	alice@example.com
4	Bob Johnson	bob@example.com

invoice Table:

invoice_id	invoice_number	customer_id	total_amount
1	INV-001	1	100.00
2	INV-002	2	150.00
3	INV-003	3	200.00
4	INV-004	4	75.00

---

SELECT *
FROM table1
CROSS JOIN table2;

Example:

SELECT * FROM customer
CROSS JOIN
invoice;

Result from Query:

Following is the result obtained by executing query on the sample database

customer_id	customer_name	customer_email	invoice_id	invoice_number	total_amount
1	John Smith	john@example.com	1	INV-001	100.00
1	John Smith	john@example.com	2	INV-002	150.00
1	John Smith	john@example.com	3	INV-003	200.00
1	John Smith	john@example.com	4	INV-004	75.00
2	Jane Doe	jane@example.com	1	INV-001	100.00
2	Jane Doe	jane@example.com	2	INV-002	150.00
2	Jane Doe	jane@example.com	3	INV-003	200.00
2	Jane Doe	jane@example.com	4	INV-004	75.00
3	Alice Brown	alice@example.com	1	INV-001	100.00
3	Alice Brown	alice@example.com	2	INV-002	150.00
3	Alice Brown	alice@example.com	3	INV-003	200.00
3	Alice Brown	alice@example.com	4	INV-004	75.00
4	Bob Johnson	bob@example.com	1	INV-001	100.00
4	Bob Johnson	bob@example.com	2	INV-002	150.00
4	Bob Johnson	bob@example.com	3	INV-003	200.00
4	Bob Johnson	bob@example.com	4	INV-004	75.00

Natural Join

The natural join performs a join based on columns with the same name in both tables.

Sample Database:

products Table:

product_id	product_name	category_id	price
1	iPhone	1	999
2	Samsung S21	1	899
3	Sony TV	2	1499
4	MacBook Pro	3	1999

categories Table:

category_id	category_name
1	Phones
2	TVs
3	Laptops

---

SELECT *
FROM table1
NATURAL JOIN table2;

Example:

SELECT * FROM products
NATURAL JOIN categories;

Result from Query:

Following is the result obtained by executing query on the sample database

product_id	product_name	category_id	price	category_name
1	iPhone	1	999	Phones
2	Samsung S21	1	899	Phones
3	Sony TV	2	1499	TVs
4	MacBook Pro	3	1999	Laptops

Self Join

The self join allows a table to be joined with itself.

Sample Database:

employee Table:

employee_id	first_name	last_name	manager_id
1	John	Smith	NULL
2	Jane	Doe	1
3	Alice	Brown	1
4	Bob	Johnson	2

SELECT *
FROM table1 AS t1
JOIN table1 AS t2
ON t1.column = t2.column;

Example:

SELECT
    e.first_name || ' ' || e.last_name employee,
    m .first_name || ' ' || m .last_name manager
FROM
    employee e
INNER JOIN employee m ON m .employee_id = e.manager_id
ORDER BY
    manager;

Result from Query:

Following is the result obtained by executing query on the sample database

employee	manager
John Smith	NULL
Jane Doe	John Smith
Alice Brown	John Smith
Bob Johnson	Jane Doe

Implementing Joins in DbSchema

DbSchema is a database management and design tool that supports SQL querying.

To implement Joins in DbSchema follow the steps mentioned below:

Inner Join

1. Open DbSchema and connect to your PostgreSQL database.
2. Create a new SQL Editor window.
3. Write the inner join query and execute it.

Left Join

1. Open DbSchema and connect to your PostgreSQL database.
2. Create a new SQL Editor window.
3. Write the left join query and execute it.

Right Join

1. Open DbSchema and connect to your PostgreSQL database.
2. Create a new SQL Editor window.
3. Write the right join query and execute it.

Full Outer Join

1. Open DbSchema and connect to your PostgreSQL database.
2. Create a new SQL Editor window.
3. Write the full outer join query and execute it.

Cross Join

1. Open DbSchema and connect to your PostgreSQL database.
2. Create a new SQL Editor window.
3. Write the cross join query and execute it.

Natural Join

1. Open DbSchema and connect to your PostgreSQL database.
2. Create a new SQL Editor window.
3. Write the natural join query and execute it.

Self Join

1. Open DbSchema and connect to your PostgreSQL database.
2. Create a new SQL Editor window.
3. Write the self join query and execute it.

Implement JOINS and Visually Manage PostgreSQL using DbSchema

DbSchema is a PostgreSQL client and visual designer. DbSchema has a free Community Edition, which can be downloaded here.

Implement JOINS

• Start the application and connect to the Postgres database.
• Navigate to SQL Editor and create a new SQL Editor window.
• Write the desired Join query and execute the query.

Conclusion

Joins are an essential aspect of working with relational databases. They enable us to combine data from multiple tables, providing a powerful way to retrieve and analyze data. By understanding the different types of joins and how to implement them in psql and DbSchema, you can enhance your data querying capabilities and perform complex operations efficiently.

References

• PostgreSQL Documentation: https://www.postgresql.org/docs/
• DbSchema Documentation: https://www.dbschema.com/documentation/

Remember to consult the official documentation of the tools you are using for the most up-to-date and detailed information.